23 papers · 1 filter
RoboDreamer: Anticipatory Humanoid Locomotion with Predictive State-Space Models
Zhe Li, Yangyang Wei, Xichen Yuan +4
Humanoid locomotion requires control policies that remain stable under imperfect sensing while exploiting temporal context for consistent motion. We present RoboDreamer, a two-stag…
Unified Condition-Action Modeling for Accurate One-Step Action Generation
Xinyu Zhou, Zikun Cai, Kuangji Zuo +7
Robot manipulation requires policies that are both accurate and efficient, as robot control must respond to changing observations under tight latency constraints. Recent diffusion…
Physics Filtering Favors the Generalization of Robot Learning
Jindou Jia, Shixuan Han, Meng Wang +8
Living organisms exhibit extraordinary adaptability to unseen environments through their intrinsic physical structures and lifelong feedback-driven learning. Endowing robots with c…
-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation
Zhe Li, Zhenzhe Zhang, Yangyang Wei +8
Humanoid household tasks often require concurrent loco-manipulation, where the robot must move, adjust posture, maintain balance, and manipulate objects as a single coordinated beh…
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation
Mengfei Zhao, Dihong Huang, Yikai Tang +12
Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on speciali…